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An Introduction to Support Vector Machines and Other Kernel-based Learning Methods John Shawe-Taylor, Nello Cristianini
Publisher: Cambridge University Press

[1] An Introduction to Support Vector Machines and other kernel-based learning methods. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Shawe-Taylor & Christianini (2004). An introduction to support vector machines and other kernel-based learning methods. [8] Nello Cristianini and John Shawe-Taylor, “An Introduction to Support Vector Machines and Other Kernel-based Learning Methods”, Cambridge University Press, 2000. Nello Cristianini, John Shawer-Taylor [2] 数据挖掘中的新方法-支持向量机 邓乃扬， 田英杰 [3] 机器学习. Christianini & Shawe-Taylor (2000). Kernel Methods for Pattern Analysis . An Introduction to Support Vector Machines and other kernel-based learning methods . Based upon the framework of the structural support vector machines, this paper proposes two approaches to the depth restoration towards different scenes, that is, margin rescaling and the slack rescaling. The results show that In [6], a new supervised machine learning method was proposed to handle such problem based on conditional random fields (CRFs), and the results had shown a promising future. Book Depository Books With Free Delivery Worldwide: Support vector machine - Wikipedia, the free encyclopedia . We follow the method introduced in [21] to solve this problem.